Back to resultsArtificial Intelligence in the Detection of Right Sided Colonic Polyp in Different Operator Experience
Primary Purpose
Colon Polyp
Status
Recruiting
Phase
Not Applicable
Locations
Thailand
Study Type
Interventional
Intervention
Artificial intellegence. CADe syste,
control
Sponsored by
About this trial
This is an interventional screening trial for Colon Polyp focused on measuring colon polyp, artificial intellegence, colonoscopy
Eligibility Criteria
Inclusion Criteria: participants age 40-80 years Exclusion Criteria: History of colonic surgery (except appendectomy) Lower gastrointestinal bleeding unstable vital sign during endoscopy of pregnancy history of inflammatory bowel disease, polyposis syndrome, colon cancer, colonic stricture, abnormal coaglulation, organ failure
Sites / Locations
- Rajavithi HospitalRecruiting
Arms of the Study
Arm 1
Arm 2
Arm 3
Arm 4
Arm Type
Active Comparator
Active Comparator
Experimental
Experimental
Arm Label
control, experienced
control, beginner
AI, experience
AI, beginner
Arm Description
Patients received colonoscopy with double insertion of right sided colon under white light by experienced endoscopist
Patients received colonoscopy with double insertion of right sided colon under white light by beginner endoscopist
Patients received colonoscopy with double insertion of right sided colon under AI by experienced endoscopist
Patients received colonoscopy with double insertion of right sided colon under AI by beginner endoscopist
Outcomes
Primary Outcome Measures
polyp detection rate
the number of polyp detected during endoscopy
Secondary Outcome Measures
type of polyp
the type of polyp detected during endoscopy
Full Information
1. Study Identification
Unique Protocol Identification Number
NCT05990218
Brief Title
Artificial Intelligence in the Detection of Right Sided Colonic Polyp in Different Operator Experience
Official Title
Efficacy of Artificial Intelligence in the Detection of Right Sided Colonic Polyp in Operators With Different Endoscopic Experience: A Randomized Control Trial
Study Type
Interventional
2. Study Status
Record Verification Date
August 2023
Overall Recruitment Status
Recruiting
Study Start Date
February 13, 2023 (Actual)
Primary Completion Date
February 12, 2026 (Anticipated)
Study Completion Date
February 28, 2026 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Rajavithi Hospital
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes
5. Study Description
Brief Summary
Colonoscopy is the gold standard modality for the detection of colonic polyp. However, miss polyp occurs especially in right sided colon. Artificial intelligence (AI) is one of the modality to improve polyp detection but the benefit of AI in operators with different endoscopic experience is still limited. This study aimed to evaluate the efficacy of AI in the detection of right sided colonic polyp in operators with different endoscopic experience by using double insertion of right side colon, back-to-back basis.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Colon Polyp
Keywords
colon polyp, artificial intellegence, colonoscopy
7. Study Design
Primary Purpose
Screening
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Model Description
Patients randomized to 4 arms: control with experienced operator, control with beginner operator, AI with experienced operator, AI with beginner operator
Masking
Participant
Masking Description
The patients were masked from being randomized to operator and endoscopic method
Allocation
Randomized
Enrollment
240 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
control, experienced
Arm Type
Active Comparator
Arm Description
Patients received colonoscopy with double insertion of right sided colon under white light by experienced endoscopist
Arm Title
control, beginner
Arm Type
Active Comparator
Arm Description
Patients received colonoscopy with double insertion of right sided colon under white light by beginner endoscopist
Arm Title
AI, experience
Arm Type
Experimental
Arm Description
Patients received colonoscopy with double insertion of right sided colon under AI by experienced endoscopist
Arm Title
AI, beginner
Arm Type
Experimental
Arm Description
Patients received colonoscopy with double insertion of right sided colon under AI by beginner endoscopist
Intervention Type
Device
Intervention Name(s)
Artificial intellegence. CADe syste,
Intervention Description
The patient received endoscopy under CADe system for polyp detection during second endoscopic withdrawal.
Intervention Type
Device
Intervention Name(s)
control
Intervention Description
The patient received endoscopy under conventional white light for polyp detection during second endoscopic withdrawal.
Primary Outcome Measure Information:
Title
polyp detection rate
Description
the number of polyp detected during endoscopy
Time Frame
during endoscopy
Secondary Outcome Measure Information:
Title
type of polyp
Description
the type of polyp detected during endoscopy
Time Frame
during endoscopy
10. Eligibility
Sex
All
Minimum Age & Unit of Time
40 Years
Maximum Age & Unit of Time
80 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria:
participants age 40-80 years
Exclusion Criteria:
History of colonic surgery (except appendectomy)
Lower gastrointestinal bleeding
unstable vital sign during endoscopy of pregnancy
history of inflammatory bowel disease, polyposis syndrome, colon cancer, colonic stricture, abnormal coaglulation, organ failure
Facility Information:
Facility Name
Rajavithi Hospital
City
Bangkok
Country
Thailand
Individual Site Status
Recruiting
Facility Contact:
First Name & Middle Initial & Last Name & Degree
Tanyaporn Chantarojanasiri, MD
Phone
0898104033
Email
chtunya@gmail.com
First Name & Middle Initial & Last Name & Degree
Tanyaporn Chantarojanasiri, MD
12. IPD Sharing Statement
Plan to Share IPD
No
Citations:
PubMed Identifier
34218329
Citation
Kamba S, Tamai N, Saitoh I, Matsui H, Horiuchi H, Kobayashi M, Sakamoto T, Ego M, Fukuda A, Tonouchi A, Shimahara Y, Nishikawa M, Nishino H, Saito Y, Sumiyama K. Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial. J Gastroenterol. 2021 Aug;56(8):746-757. doi: 10.1007/s00535-021-01808-w. Epub 2021 Jul 3.
Results Reference
background
Learn more about this trial
Artificial Intelligence in the Detection of Right Sided Colonic Polyp in Different Operator Experience
We'll reach out to this number within 24 hrs